Nasdaq, Inc. (NDAQ) Earnings Call Transcript & Summary

I'm Ashish Sabadra, and I cover information services and exchanges here at RBC. We are really excited to host Sarah, CFO of Nasdaq. Sarah, thanks for giving us this opportunity.

Thanks for having me.

Thank you. I'll start off on the topic that everybody is focused on at the tech conference, which is Gen AI. So maybe talk about both the top line and bottom line. So on the top line perspective, maybe if we can talk about the proprietariness and how embedded within your client workflows you are, but also monetization opportunity. How do you think about monetization from Gen AI? And then we also would like to cover on the bottom line side, how do we think about investment, but also efficiency. So maybe if you want to start with the top line and monetization opportunity.

No, that's great. I appreciate the question. So we feel really good about Gen AI for Nasdaq. And so if you try to look at why would we, I go back to 10 years ago, we went into cloud. And 9 years ago, we went into AI, algorithmic AI. By the time you have that, you are like preparing your data for Gen AI. And so we started doing that a long time ago. Some people have to do some major investments to do that. The second thing about data that we have is contributory data, which is moted. And I think that's extraordinarily important as a differentiator because Gen AI is lovely, but it works better on a lot of data that can be done individually by a lot of people, but our data is only accessible by those who contribute it. So I'll give you 2 examples of that, contributory data of Verafin. And that's $10 trillion or over $10 trillion in total assets of banks across 2,700 banks, took us 15 years to assemble the data set. And so somebody can maybe do it in 5 or in 8, but it's not something that can be done in 2 years. And we're not sitting on those laurels. We are bringing Gen AI, and I'll come back to that as to how we monetize there. Another example of contributory data with the investment at 1,000 and probably many of you in the room, allocators use it around 89,000 strategies. By the time you have that for public equities, you can add private equities, but being embedded in workflows with that contributory data, you can't really go find that data somewhere else. Therefore, you buy it from us. We like that. By the time you have that, you can start doing Gen AI on top of that. And I'll use Verafin as an example of what we have done there. And we have done first, a Copilot with Gen AI, but that's still human in the loop at the bank. And then an agent on sanctions that gives our banks the opportunity not to have a person touch 80% of the sanctions. That's extremely valuable because now we're talking about our banks, not only having less fraud, thanks to us, which has an incredible ROIC and that's done with algorithmic AI, but also being able to have efficiencies on the base. And you can ask the banks, I used to be a bank CFO at UBS and at Chase, there are hundreds of people in compliance. So we are not addressing some small groups of efficiencies, but large group of efficiencies. So we are seeing that on that, the banks are willing theoretically to pay. And the model that we are using is Copilots are embedded and are part of our net retention apparatus, adding value to our clients so that we can increase the pricing or get upsells. However, the upsells would be the agents. The agents are not like you have it, you need to pay for it to just have it on your platform, but above a certain volume. So you get to use it, but build the habituation at the bank and then pay for it. So we do believe that the revenue that is influenced by Gen AI is across all of Nasdaq. I just gave you 2 examples, but I could go into each of our product and that we have opportunity to upcharge that at the beginning, it's important to give the arbitration. In terms of the bottom line, we are also doing it, and this was in the products, we call it on the business. So whether you are a finance function, legal function, the product development, everybody is engaged in Gen AI, and we are asking people to put real efficiencies in the budget. We have -- when we increased the number from $80 million to $140 million, we had already overachieved the $80 million. But we also said we're going to do what we had done as efficiencies just in the fintech businesses beyond that. And we will have benefits of Gen AI in there. And so we are delivering some of those benefits already. So there are some dollars of efficiencies that are falling to the bottom line that are already linked to Gen AI in client success, in the PDLC, and we are asking everybody everywhere to do it. So I can show you the ones in finance and everybody everywhere can give you theirs. And that will continue to be an efficiency play that we continue to have.

That's great color. And we will talk about the cost synergies on the fintech side. But before we do that, I just wanted to drill down on some of the products. So particularly Verafin, the example that you gave, I want to talk about the business there. You've had a pretty big uptick in enterprise signing, both Tier 1 and Tier 2 clients. Can you talk about what's really driving those? And can you also talk about your pipeline going forward for more Tier 1 and Tier 2 customers?

Yes. So Verafin is a great growth engine to calibrate, so far this year in 3 quarters, we have 3x the amount of signings in enterprise, and that's 2x on the ACV of signing. So that is a moment that we've all been waiting for, and there is more to come. And when you look at the cross-sell pipeline, which is not just Verafin, of course, it stayed steady at that 15%-ish level, which means that we are replenishing the pipeline. We have a bunch of POCs that are in place, including one that is in Europe, which will open a new market for us, but we also have some additional Tier 1s and Tier 2s in the U.S. that we continue to build the momentum for. So we feel very well positioned. We're getting tremendous client feedback on the way we are utilizing the data, we are connected to 70 core banking system in that business, which is really important to capture the 2,700 banks. But that's out of 10,000 banks. So we have plenty of other banks we could get. And for the large banks, we are viewed as very innovative. And I had with one of them the discussion of build versus buy for them. And I think they have all come to the realization that you cannot build the data set that we have. And therefore, the only way to get the small banks input into the big banks is us.

That's true. I think the network effect is so evident, particularly in the case of Verafin. Just shifting gears on the fintech side, talking about the capital market technology, we saw a pretty good improvement there, 13% growth in the third quarter. What's driving that resumption? And can you help us understand how are you thinking about the growth across the different businesses within that, which is Market Tech, Calypso and the trade management services?

Yes. So once again, and I'm going to address Gen AI in each of them just to make sure that I don't just talk about it for Verafin because we're very excited about it across our business. So when you try to think about Calypso or trade management services or Market Tech, now you're into core infrastructure. And if you're trying to think about Calypso, for example, we think that the convergence of tokenization and Gen AI. Any bank is looking at it as if I am not using a provider, I should really think about that. I think it maybe take exception for like 3 or 4 banks whose differentiation is that, and they have built fantastic systems. But for the great majority of bank, you're not going to add tokenization in your Excel. And so when you're looking at Calypso having done already a collateral POC, that is something which they will rely on people like us to do. When you're looking at core infrastructure, you're also looking at something that's very, very difficult to displace with something that you can do yourself. It's not a simple workflow to put together. So could you imagine an agent that starts doing free trade, trade collateral management and with all of the connectivity to all of the things that need to work for that to happen. There is no little agent that does that, not even a good agent. And so we feel really good about the fact that we are entrenched, but we're also modular and therefore, easy to add. And now that we have a cloud offering, it's really the foundation that we needed for Calypso to be able to do even more for our clients with that. If you then go into Market Tech, Market Tech, we are, I would say, the Rolls-Royce of Market Tech systems. To calibrate, we own and operate about 20 exchanges across the Nordics and the U.S., a bit in Canada. But we operated for others. So think of it as SaaS in a box for 130 plus. So that means 110 are done for others. So we are very good at that. We have benefited from some of the new entrants in the space, especially on digital. So -- but not just digital, but new players can use our technology and very much appreciate that. If you're looking at the last piece, trade management services, that's very different. That is connectivity that is really leveraging the trend of everything is faster. And in trading, the nanoseconds differentiations make a difference. People hedge funds, in particular, will pay a fair bit for that. We intentionally added space and power with our partner, Equinix, and we've been able to monetize that, and you're seeing that in our results.

That's great color. Just shifting gears and talking about the last segment within fintech would be particularly regulatory tech. So as you think about the regulatory environment, how do you think about like are the clients still waiting for some clarity on the regulatory side? How does that influence the regulatory tech? And then if you could also talk about some of the dynamic around professional services and some of the headwinds, but also tailwinds going forward as we think about the top line growth there.

Yes. So one more thing about the regtech, this includes our Solovis business as well as AxiomSL. So talking first about the regulatory trend. At this point, there is good confidence that this government will do what is called smart regulation. So there is no indication that there will be no regulation as opposed to smart regulation. That's very important for us because we can adapt to any regulation as long as there is some regulation. We do think that Basel III, which is a big element of regulation that was well expected by the banks will come. There is a date that is in December on the schedule. That being said, with the shutdown, could it move into January? Absolutely or even February. So do I have a specific date? No. But do I believe that we will have the clarity we were looking for, for our clients to engage yes. More importantly, do our clients act as if they believe that? Absolutely. And so we are seeing that pipeline, and that is very helpful. across the world, our solutions are very much adopted. I think it's helpful to remind the audience of like what we announced in the third quarter, which is this large bank, which displaced a competitor, put us as Axiom in place in multiple regions. And so that confidence that we're getting, that's one happened to be a cross-sell to is very much what we hoped is to become a larger partner to banks, not just in the U.S. but international banks and having the coverage of 55 countries, 110 regulators, 5,500 reports, 3,000 updates every year. Again, that's very difficult to replicate. And if you're thinking Gen AI, what's your differentiation there? It's data lineage. So not only do we have the data for the AxiomSL reports, but we actually have the lineage that goes with it. And if you ask a bank CFO, which I was one, what is the most difficult thing to do in bank infrastructure, it's data lineage. And so whereas theoretically, once you have the data in perfectly orderly form, you could do a reg to code. And you will never want to be responsible for those 3,000 updates a year if you're large international banks in all of those countries. And you don't even have the data organized in that form without using our tools. So we feel very good about the protections we have. And again, not resting on those laurels, but adding Gen AI on top of that, on top of surveillance to make sure that we continue to bring innovation to our markets. And surveillance, very nice performance. That's a business that has benefited from the Adenza acquisition. The leader of regtech is an Adenza leader who has brought a lot of energy. And you're hearing more about surveillance than you did in the past, and that's for a good reason because we are doing a lot with those road maps and our clients are rewarding us with more business.

That's great. And maybe just a follow-up there. Obviously, you gave multiple examples of cross-selling and successes that you've had across all the segments within fintech. You've already guided to like $100 million of cross-sell synergies by 2027. So maybe just any more color on the progress that you're making towards the cross-sell? How should we see that momentum pick up, particularly on the cross-sell side?

Yes. So we have continued to share, as you have just mentioned, the percentage of our fintech pipeline that is cross-sell. And whereas we had said that we wanted it to be around 10%, 11% or a bit more than that, if possible. We've consistently now for some time, given you a 15% or above type of number, which we feel is a very good number. It does take some time for that to translate into revenue, but we feel we're very well positioned to meet or exceed the $100 million.

That's great color. Just moving on to the Capital Access business, talking about the listing. Obviously, from your exchange perspective, you have really good visibility on the listing business. How do you think about the listing pipeline? And then how should we think about that contributing to your revenue stream going forward?

Yes. So if you think about Capital Access platform, the listings franchise is very much part of our brand name. I think if you say Nasdaq, you say Power Innovation, Nasdaq 100. And so that brand, which is now a top 100 global brand, it's very, very rare to have a B2B brand that is actually a top 100 global brand by Interbrand. Like when you look at that survey, you've got us ahead of Tiffany. You've got us with the Amazon's and the Nike's and all of the things which you associate big brands. And so Nasdaq is that brand, the listing franchise is very much associated with that brand, and we feel very fortunate to have that recognition, but we also work on it every day. And this is both the listings and the switches. We have had a very good momentum in both. And we are really excited about the value proposition that we provide to our clients. So the quality of trading, of course, the community, it's a very good group to be part of to be around -- so we've got about half of the market cap of the U.S., about 20% of the market cap of the world that is on Nasdaq. And when you look at who that group of, it has, of course, the Mag 7, but all of the players that are in Nasdaq 100 and beyond are a tremendous company. We also, I would say, go out of our way to use our marketing dollars towards helping the brands of our clients. And so we're very involved with our clients. I spend time with our CFOs. And we also advocate on behalf of our listed companies, especially at times like now where there is advocate that can be done in a very productive way. So we feel good about the franchise. We're well positioned. We have a nice pipeline, and it's part of the flywheel. It does mean that we are able to have the closing cost in Market Services. And so we have some Data businesses associated with this and of course, the Index business, which is now an $800 billion business and the revenue has multiplied by 8 in 8 years.

Yes. No, absolutely. And that was going to be my follow-up question. Obviously, you talked about Nasdaq Index being such a strong franchise. How do you think about expanding that into new products or international markets? How do we think about the shift towards ETP? Any color on that front? But essentially expanding that product suite, obviously, a very strong franchise.

Yes. So Index is a great business. And if you go back to 2017, it was $100 million franchise, about $100 billion of AUM. It was this little thing nobody talked about. And Adena rightfully so deployed a lot of investments in that business, which still continues to have tremendous margins, by the way, even after the level of investments we have done. This is a fantastic high-margin business, but also high-growth business. We have 3 vectors of growth. One is continuing to add new products. So both NDX-related and non-NDX related. And that gives us also resilience in terms of inflows coming at times when people are looking for Nasdaq 100 or Nasdaq 100 related. We can provide yield to some of the products that are done around NDX or we can be in totally different things that are inadequation with our brand Nasdaq. And so you want the Gen AI item, you can do it. If you want the data center, if you want -- like we have lots of products that we build in partnership with asset management clients. Second is international. We used to be very much U.S. We believe that both in the queue in NDX-related products and beyond that, we can certainly add value to asset managers across the world. And we've had very good growth there. And then the last one is institutional and through our asset managers, our indexes so far end up in the hands of retail in general. And institutional is a big opportunity. We are still underpenetrated in that opportunity. We've put some investments to make sure that we continue to ramp up in that space.

That's great color. You mentioned a couple of times about the data business That data business has been growing really fast. And I think some of the flywheels that you get from listing and everything else. Maybe just any other incremental color that you want to add on the data business. And then as we think about that proprietariness as well, like any color there as well?

Yes. So think about our Data businesses in 2 parts. We've got regulated data. So everybody who's got an iPhone on the table and is checking the stock market is looking at Nasdaq data. And so if you're looking at it in Excel, you're still using Nasdaq data. And so if you are doing it through a retail brokerage and buying and selling, you're still using Nasdaq data for very good majority of the cases. If you're now sitting in Asia or in Europe and you want to trade in the U.S., you're still using Nasdaq data very often, that was an example I gave yesterday on eToro and whereas we have already the U.S., we just added a data set with 210 stocks that are in the Nordics because actually, if you're sitting in Oslo or in Stockholm, you might want to invest in the fantastic local companies that you have, you have a home bias, but you also want to invest in Apple or in any of the U.S. stocks that are here. And so that's the regulated data. Then we have another data set, which is whatever data set we can combine that gives alpha to a hedge fund, for example. And that could be -- if you want to invest in health care, we could partner with a health care company on getting some data from a health care company, and we can then marry that with some of our data to provide alpha opportunities to our clients, which, of course, can give us a good amount of pricing so that they can have access to that proprietary set.

That's very helpful color. Maybe just going on to your Market Services or the exchange business. You recently filed proposal for tokenized securities. Can you talk about like how do you expect to benefit from a trading volume or capital liquidity margining perspective? Or how is this -- how do you expect this whole exchange business to evolve? There's a lot of talk about tokenization. How will it be disruptive or additive to your existing franchise?

So we feel the proposal that we have put in place is additive. What's very important is to respect what exists. What exists is investor protection, market integrity, transparency, depth of liquidity pools. So you've got a U.S. capital markets that actually functions, functions extremely well at speeds that are extraordinary. And we want to make sure that we embrace innovation while embracing preserving what exists. And so one of the guiding principle in our proposal was let's not break the liquidity pool, and let's make sure that each equity instrument is what it is. But now I think it is very helpful to provide the option for the settlement to be either in traditional form or in tokenized form. And that's exactly what our proposal is. And so at the time of the trade, you can indicate whether you want a settlement in token form or in traditional form. And that enables you to have the potential advantages of a token, which could be mobility, you could potentially, at some point, have speed, although right now, we are not changing the settlement plus 1 all good. And you certainly could see some applications in collateral management that would make it good. So you could decide whether you want to do netting, but you would have opportunities to do that. And so we do think that it opens the aperture and it's really additive because it did not hurt the liquidity pool and the investor protections.

Yes. No, that's great color. Just moving on to the cost synergies. You mentioned that upfront as well, how Gen AI is driving a lot of efficiencies for you. You've already surpassed your $140 million of synergy guidance and hitting more closer to $150 million year-to-date. How do we think about the synergy in the context of that 5% to 8% expense growth as well? So if you can help us understand how do we think about further synergies and also the expense growth?

Yes. So we've got a very specific expense guidance for this year. So that basically is supportive of the revenue growth that we have. So the way you should think about it is there are really 3 parts to the expense, a structural part, which benefits from the efficiencies and is obviously also reflecting inflation and merit and other things that come through. Then you have volume related. So by definition of many of our products being in the cloud, and we have marginal costs, which we can work on having unit economics efficiencies. But by definition, more business equals more cost, but in a very productive way and at a high margin, incremental margin. And then we have the investments we are making. We're spending a lot of time in making sure that we are using, for example, Gen AI and making those investment more efficient. But we also spend a lot of time in capital allocation in our organic investments to make sure that we're deploying those dollars in ways that will both create the trust in Nasdaq brand because it's definitely a tenet of our brand, but also the innovation, which could be the R&D. I talked about cloud 10 years ago. We didn't have a good business case towards that. But we did it, and we're so glad we did. And so there are things in R&D that absolutely need to be maintained. And in between, you've got the shareholders' benefit. So we have Horizon 1 and Horizon 2, Horizon 1 being twice your investment return in 3 years, Horizon 2 in 5 years.

That's great. And maybe I wanted to end with a question on capital allocation. You talked about a lot about driving growth while investing organically, but how do -- like with leverage now at 3.1 turns, expected to be 3 turns by end of the year ahead of your schedule, how are you thinking about capital allocation going forward? And particularly in light of like the stock has pulled back a bit, how do you think about buyback versus M&A or other uses of capital, deleveraging, including?

Yes. So I would say what you're about to hear is very much a continuity of what I have said and what Adena has said, we have a focus on organic growth. So before you get to our $2 billion plus of free cash flow, we have invested well in the business. And that's incredibly important for the resiliency. The second part is we have a dividend that is progressive, and we are continuing to do that. And then comes share repurchase, debt repurchase. We are at the point where we can be very smart and optimized about thinking about both of them. When you look at it in acquisition dilution, some of those tranches of debt look attractive, but we're doing math. And so you will continue to see us optimize both in share repurchase because we like our stock and in debt repurchases. And then could there be a bolt-on? Of course, there could be, but our focus right now is on organic.

Okay. That's great. We'll leave it there. Thank you again. Thanks, everyone, for joining, and thank you, Sarah, for giving us this opportunity.